library(tidyverse)
library(purrrlyr)
library(plotly)
library(themebg)

# x <- dirr::get_rds("../data/tidy")
x <- dirr::get_rds_s3("warfarin-annual-report", "data/tidy/")
p <- data_daily %>%
    filter(warfarin_day <= 10) %>%
    dmap_at("warfarin_day", as.integer) %>%
    left_join(data_warfarin[c("millennium.id", "group", "initiation", "indication_group")], by = "millennium.id") %>%
    ggplot(aes(x = factor(warfarin_day), y = med.dose, color = group)) +
    geom_boxplot() +
    xlab("Day of therapy") +
    ylab("Warfarin dose (mg)") +
    scale_color_brewer("Group", palette = "Set1") +
    theme_bg()

ggplotly(p, dynamicTicks = TRUE)

Distribution of warfarin dose by day of therapy

p <- data_daily %>%
    filter(warfarin_day <= 10,
           med.dose > 0,
           !is.na(inr)) %>%
    # dmap_at("warfarin_day", as.integer) %>%
    left_join(data_warfarin[c("millennium.id", "group", "initiation", "indication_group")], by = "millennium.id") %>%
    ggplot(aes(x = med.dose, y = inr)) +
    geom_point(aes(color = group), shape = 1) +
    xlab("Warfarin dose (mg)") +
    ylab("INR") +
    scale_color_brewer("Group", palette = "Set1") +
    theme_bg()

ggplotly(p, dynamicTicks = TRUE)

Relationship between warfarin dose and INR